Swarmalators with Stochastic Coupling and Memory

Schilcher, Udo; Schmidt, Jorge F.; Vogell, Arke; Bettstetter, Christian

doi:10.1109/acsos52086.2021.00028

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…These studies have enfolded some captivating dynamics. More studies like oscillatory behavior with repulsive short-range interaction [49], active phase wave with attractive phase coupling [50], dynamics under stochastic coupling and memory [51], and mean-field limit [52] have enriched this field which we mention here and were unable to discuss in our main text.…”

Section: Model Of Swarmalators -mentioning

confidence: 99%

Dynamics of swarmalators: A pedagogical review

Sar

Ghosh

2022

EPL

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Swarmalators have emerged as a new paradigm for dynamical collective behavior of multi-agent systems due to the interplay of synchronization and swarming that they inherently incorporate. Their dynamics have been explored with different coupling topologies, interaction functions, external forcing, noise, competitive interactions, and from other important viewpoints. Here we take a systematic approach and review the collective dynamics of swarmalators analytically and/or numerically. Long-term states of position aggregation and phase synchronization are revealed in this perspective with some future problems.

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Section: Model Of Swarmalators -mentioning

confidence: 99%

Dynamics of swarmalators: A pedagogical review

Sar

Ghosh

2022

EPL

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“…This swarmalator model is being used as a spring-board to further study the collective behavior of swarmalators. The effects of pinning [11], forcing [12], and various types of coupling (delayed [13], finite-range [14] stochastic [15], mixed sign [16][17][18][19]) as well as other phenomena/scenarios [20][21][22][23][24][25] have been explored. For reviews of swarmalators, see [26,27].…”

Section: Introductionmentioning

confidence: 99%

Swarmalators with thermal noise

Hong¹,

O’Keeffe²,

Lee³

et al. 2023

Preprint

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We investigate a population of swarmalators, a mobile version of phase oscillators that both sync in time and swarm through space. We focus on a XY-type model of identical swarmalators running on a one-dimensional ring and subject to thermal noise. We uncover four distinct collective states, some of which capture the behavior of real-world swarmalators such as vinegar eels and sperm. Among these, the most intriguing is the 'mixed state', which blends two of the other states. We present a comprehensive phase diagram from the Fourier mode analysis with a high accuracy, which is in excellent agreement with numerical simulation results. Our model serves as a tractable toy model for thermal systems that both self-synchronize and self-assemble interdependently.

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Volatile Memory Motifs: Minimal Spiking Neural Networks

Neves

Timme

2023

IEEE Access

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Swarmalators with Stochastic Coupling and Memory

Cited by 4 publications

References 17 publications

Dynamics of swarmalators: A pedagogical review

Dynamics of swarmalators: A pedagogical review

Swarmalators with thermal noise

Volatile Memory Motifs: Minimal Spiking Neural Networks

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